{"id":1416,"date":"2023-09-11T18:59:17","date_gmt":"2023-09-11T23:59:17","guid":{"rendered":"https:\/\/sites.owu.edu\/geog-291\/?p=1416"},"modified":"2023-09-11T18:59:17","modified_gmt":"2023-09-11T23:59:17","slug":"coleman-week-3","status":"publish","type":"post","link":"https:\/\/sites.owu.edu\/geog-291\/2023\/09\/11\/coleman-week-3\/","title":{"rendered":"Coleman-Week 3"},"content":{"rendered":"

Ch. 4<\/span><\/p>\n

Mapping the density of your study will help allow you to better see patterns and other important ideas. Something you can do to map density is create areas of color with density value that can be demonstrated by creating a key. You can use GIS to map density points which are usually points of surface. GIS can allow you to map the density of features or of feature values.These two different approaches yield different results and info. There are ultimately two ways of mapping density according to the book. The first way is you can create a density map based on features summarized by defined areas(s). The second way is you can create a density map by creating a density surface.<\/span><\/p>\n

For mapping density by defined arena it can be mapped geographically using a dot map or you can calculate a density value for each area. For mapping density by surface, you usually create in GIS a raster layer. Each cell in the layer gets a density value, such as number of businesses per square mile, based on the number of features within a radius of the cell. Comparing methods: you should map density by areas if you have data already summarized by area, or lines or points you can summarize by area(output, trade-offs). This method doesn\u2019t pinpoint exact centers of density, especially for large areas. You should map density by surface if you have individual locations, sample points or lines. So it seems that by precision for small areas then pick surface to map density and large areas with less precision do area.\u00a0<\/span><\/p>\n

Must be able to calc density values per area: pop density=total pop\/(area\/?) Dots can help a lot with density.You can use GIS to summarize features or feature values.GIS uses two methods for calculating the cell values needed for mapping density:simple method\/calc and weighted\/calc method. You can display density using patterns or colors. I like how darker shades mean more dense and lighter means less dense.<\/span><\/p>\n

Ch.5<\/span><\/p>\n

People map what is inside an area in order to monitor what is happening inside it, or to compare several areas based on what\u2019s inside each. By summarizing what\u2019s inside these areas, allows people to compare areas to figure out more of an understanding for a feature. You can access a single area or find out what is inside each of the several areas in your map.\u00a0<\/span><\/p>\n

Single area: When you find what\u2019s inside a single area, it will let you monitor activity or summarize info about the area. Ex:a service area around a central facility, such as a library district.\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0<\/span><\/p>\n

Multiple areas: This method would let you compare the areas that you look inside of. Ex: contiguous, such as zip codes or watersheds.<\/span><\/p>\n

Discrete features: these are unique and identifiable features. Ex: crimes or streams<\/span><\/p>\n

Continuous features: represent seamless geographic phenomena. Ex: classes or categories<\/span><\/p>\n

After you get the info from the analysis, you must determine which method to use.\u00a0<\/span><\/p>\n

Ex: list, count or summary?<\/span><\/p>\n

You can use GIS to select features that are either completely or partially inside the area or even not at all.\u00a0<\/span><\/p>\n

There are three different ways to calculate or find out what is inside your intended area.<\/span><\/p>\n

    \n
  1. You can create a map showing the boundary of the area and the features, this is called drawing areas and features. Good for visual approach. Need a dataset containing the boundary of the area or areas and a dataset containing the features.<\/span><\/li>\n
  2. You can specify the area and the layer containing features and GIS can select a subset of the features inside the area, this is called selecting the features inside the area. Good for getting a list or summary. It is also good for finding what\u2019s within a given distance of a feature. Need the dataset with the features and any important attributes.<\/span><\/li>\n
  3. Overlaying the areas and features allows GIS to combine the area and the features to create a new layer with the attributes of both or compare the two layers. Good for finding which features are in each of several areas.<\/span><\/li>\n<\/ol>\n

    There was another way, but these seemed like the most important and relevant. Overlaying areas and features is an important method. **Vector method and raster method<\/span><\/p>\n

    Ch.6<\/span><\/p>\n

    A map can help you find what is nearby. To find what\u2019s nearby, you can measure straight-line distance, measure distance or cost over a network, or measure cost over a surface. What\u2019s nearby\u00a0 can be based on a set distance you specify, or on travel to or from a feature.\u00a0<\/span><\/p>\n

    Distance is one way to measure how close something is nearby. You can also measure what is nearby using cost. Time is one of the most common costs.Other costs include money. These are referred to as travel costs. You can specify a single range or several ranges when looking to map something nearby. For multiple ranges, you can create rings. Ex: sonar, but the book says inclusive rings. Other ways to help compare distances are distinct bands.\u00a0<\/span><\/p>\n

    The main three ways to find what is nearby are:<\/span><\/p>\n

      \n
    1. Straight-line distance<\/span><\/li>\n
    2. Distance or cost over a network<\/span><\/li>\n
    3. Cost over a surface<\/span><\/li>\n<\/ol>\n

      These methods all vary and have several pros and cons which are around page 467 for reference. You will have to choose which method based on your map and what you dataset is as well as what you are trying to find. Once you have the info, you can make a map either including the stuff nearby or if it is separated.<\/span><\/p>\n","protected":false},"excerpt":{"rendered":"

      Ch. 4 Mapping the density of your study will help allow you to better see patterns and other important ideas. Something you can do to map density is create areas of color with density value that can be demonstrated by creating a key. You can use GIS to map density points which are usually points of surface. GIS can allow you to map the density of features or of feature values.These two different approaches yield different results and info. There are ultimately two ways of mapping density according to the book. The first way is you can create a density map based on features summarized by defined areas(s). The second way is you can create a density map by creating a density surface. For mapping density by defined arena it can be mapped geographically using a dot map or you can calculate a density value for each area. For mapping density by surface, you usually create in GIS a raster layer. Each cell in the layer gets a density value, such as number of businesses per square mile, based on the number of features within a radius of the cell. Comparing methods: you should map density by areas if you have data already summarized by area, or lines or points you can summarize by area(output, trade-offs). This method doesn\u2019t pinpoint exact centers of density, especially for large areas. You should map density by surface if you have individual locations, sample points or lines. So it seems that by precision for small areas then pick surface to map density and large areas with less precision do area.\u00a0 Must be able to calc density values per area: pop density=total pop\/(area\/?) Dots can help a lot with density.You can use GIS to summarize features or feature values.GIS uses two methods for calculating the cell values needed for mapping density:simple method\/calc and weighted\/calc method. You can display density using patterns or colors. I like how darker shades mean more dense and lighter means less dense. Ch.5 People map what is inside an area in order to monitor what is happening inside it, or to compare several areas based on what\u2019s inside each. By summarizing what\u2019s inside these areas, allows people to compare areas to figure out more of an understanding for a feature. You can access a single area or find out what is inside each of the several areas in your map.\u00a0 Single area: When you find what\u2019s inside a single area, it will let you monitor activity or summarize info about the area. Ex:a service area around a central facility, such as a library district.\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 Multiple areas: This method would let you compare the areas that you look inside of. Ex: contiguous, such as zip codes or watersheds. Discrete features: these are unique and identifiable features. Ex: crimes or streams Continuous features: represent seamless geographic phenomena. Ex: classes or categories After you get the info from the analysis, you must determine which method to use.\u00a0 Ex: list, count or summary? You can use GIS to select features that are either completely or partially inside the area or even not at all.\u00a0 There are three different ways to calculate or find out what is inside your intended area. You can create a map showing the boundary of the area and the features, this is called drawing areas and features. Good for visual approach. Need a dataset containing the boundary of the area or areas and a dataset containing the features. You can specify the area and the layer containing features and GIS can select a subset of the features inside the area, this is called selecting the features inside the area. Good for getting a list or summary. It is also good for finding what\u2019s within a given distance of a feature. Need the dataset with the features and any important attributes. Overlaying the areas and features allows GIS to combine the area and the features to create a new layer with the attributes of both or compare the two layers. Good for finding which features are in each of several areas. There was another way, but these seemed like the most important and relevant. Overlaying areas and features is an important method. **Vector method and raster method Ch.6 A map can help you find what is nearby. To find what\u2019s nearby, you can measure straight-line distance, measure distance or cost over a network, or measure cost over a surface. What\u2019s nearby\u00a0 can be based on a set distance you specify, or on travel to or from a feature.\u00a0 Distance is one way to measure how close something is nearby. You can also measure what is nearby using cost. Time is one of the most common costs.Other costs include money. These are referred to as travel costs. You can specify a single range or several ranges when looking to map something nearby. For multiple ranges, you can create rings. Ex: sonar, but the book says inclusive rings. Other ways to help compare distances are distinct bands.\u00a0 The main three ways to find what is nearby are: Straight-line distance Distance or cost over a network Cost over a surface These methods all vary and have several pros and cons which are around page 467 for reference. You will have to choose which method based on your map and what you dataset is as well as what you are trying to find. Once you have the info, you can make a map either including the stuff nearby or if it is separated.<\/p>\n","protected":false},"author":2209,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[4],"tags":[],"class_list":["post-1416","post","type-post","status-publish","format-standard","hentry","category-course-student-work"],"_links":{"self":[{"href":"https:\/\/sites.owu.edu\/geog-291\/wp-json\/wp\/v2\/posts\/1416","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/sites.owu.edu\/geog-291\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/sites.owu.edu\/geog-291\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/sites.owu.edu\/geog-291\/wp-json\/wp\/v2\/users\/2209"}],"replies":[{"embeddable":true,"href":"https:\/\/sites.owu.edu\/geog-291\/wp-json\/wp\/v2\/comments?post=1416"}],"version-history":[{"count":1,"href":"https:\/\/sites.owu.edu\/geog-291\/wp-json\/wp\/v2\/posts\/1416\/revisions"}],"predecessor-version":[{"id":1417,"href":"https:\/\/sites.owu.edu\/geog-291\/wp-json\/wp\/v2\/posts\/1416\/revisions\/1417"}],"wp:attachment":[{"href":"https:\/\/sites.owu.edu\/geog-291\/wp-json\/wp\/v2\/media?parent=1416"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/sites.owu.edu\/geog-291\/wp-json\/wp\/v2\/categories?post=1416"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/sites.owu.edu\/geog-291\/wp-json\/wp\/v2\/tags?post=1416"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}